The present article outlines progress made in designing an intelligent information system for automatic management and knowledge discovery in large numeric and scientific databases, with a validating application to th...The present article outlines progress made in designing an intelligent information system for automatic management and knowledge discovery in large numeric and scientific databases, with a validating application to the CAST-NEONS environmental databases used for ocean modeling and prediction. We describe a discovery-learning process (Automatic Data Analysis System) which combines the features of two machine learning techniques to generate sets of production rules that efficiently describe the observational raw data contained in the database. Data clustering allows the system to classify the raw data into meaningful conceptual clusters, which the system learns by induction to build decision trees, from which are automatically deduced the production rules.展开更多
There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mi...There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mining has become an urgent problem to be solved. On the base of analysis and study of existing research results, the united model of knowledge discovery state space （UMKDSS） is presented, and the structured data mining and the complex type data mining are associated together. UMKDSS can provide theoretical guidance for complex type data mining. An application example of UMKDSS is given at last.展开更多
Important Dates Submission due November 15, 2005 Notification of acceptance December 30, 2005 Camera-ready copy due January 10, 2006 Workshop Scope Intelligence and Security Informatics (ISI) can be broadly defined as...Important Dates Submission due November 15, 2005 Notification of acceptance December 30, 2005 Camera-ready copy due January 10, 2006 Workshop Scope Intelligence and Security Informatics (ISI) can be broadly defined as the study of the development and use of advanced information technologies and systems for national and international security-related applications. The First and Second Symposiums on ISI were held in Tucson,Arizona,in 2003 and 2004,respectively. In 2005,the IEEE International Conference on ISI was held in Atlanta,Georgia. These ISI conferences have brought together academic researchers,law enforcement and intelligence experts,information technology consultant and practitioners to discuss their research and practice related to various ISI topics including ISI data management,data and text mining for ISI applications,terrorism informatics,deception detection,terrorist and criminal social network analysis,crime analysis,monitoring and surveillance,policy studies and evaluation,information assurance,among others. We continue this stream of ISI conferences by organizing the Workshop on Intelligence and Security Informatics (WISI’06) in conjunction with the Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD’06). WISI’06 will provide a stimulating forum for ISI researchers in Pacific Asia and other regions of the world to exchange ideas and report research progress. The workshop also welcomes contributions dealing with ISI challenges specific to the Pacific Asian region.展开更多
Knowledge discovery from data directly can hardly avoid the fact that it is biased towards the collected experimental data, whereas, expert systems are always baffled with the manual knowledge acquisition bottleneck. ...Knowledge discovery from data directly can hardly avoid the fact that it is biased towards the collected experimental data, whereas, expert systems are always baffled with the manual knowledge acquisition bottleneck. So it is believable that integrating the knowledge embedded in data and those possessed by experts can lead to a superior modeling approach. Aiming at the classification problems, a novel integrated knowledge-based modeling methodology, oriented by experts and driven by data, is proposed. It starts from experts identifying modeling parameters, and then the input space is partitioned followed by fuzzification. Afterwards, single rules are generated and then aggregated to form a rule base, on which a fuzzy inference mechanism is proposed. The experts are allowed to make necessary changes on the rule base to improve the model accuracy. A real-world application, welding fault diagnosis, is presented to demonstrate the effectiveness of the methodology.展开更多
人工智能科学(Artificial Intelligence for Science,AI4S)作为近年来兴起的交叉学科范式,通过现代信息技术,以数据驱动的方式推动科学发现与知识服务创新。立足图书馆事业发展,从图书馆学视角去认知什么是AI4S、洞察AI4S与发展图书馆...人工智能科学(Artificial Intelligence for Science,AI4S)作为近年来兴起的交叉学科范式,通过现代信息技术,以数据驱动的方式推动科学发现与知识服务创新。立足图书馆事业发展,从图书馆学视角去认知什么是AI4S、洞察AI4S与发展图书馆服务的关系、拥抱AI4S带给图书馆服务的变革影响等内容具有重要价值。研究发现,AI4S与图书馆发展有着双向赋能的耦合逻辑链路。AI4S已在图书馆界得到了应用,在服务模式、服务能力、服务价值等方面深刻地变革影响着图书馆服务。展开更多
为研究地质学领域的大数据和人工智能研究现状、热点和前沿,在中国知网(CNKI)核心期刊和Web of Science(WoS)核心数据库收集了2000—2022年相关中文文献3600篇、英文文献1803篇,利用社区结构分析软件CiteSpace,从合作作者、研究国家、...为研究地质学领域的大数据和人工智能研究现状、热点和前沿,在中国知网(CNKI)核心期刊和Web of Science(WoS)核心数据库收集了2000—2022年相关中文文献3600篇、英文文献1803篇,利用社区结构分析软件CiteSpace,从合作作者、研究国家、研究机构、关键词聚类、关键词时空分布图谱等进行可视化分析,并统计了2021—2022年间,地质学领域国际顶级期刊(综合影响因子10以上)的文献进行前沿分析。分析结果表明,近10年内该研究领域全球累计发文量激增,以中国为代表的亚洲国家和以美国为代表的欧美国家研究为主,双方累计发文量相差不大,论文中介中心性欧美国家普遍较高。我国研究机构之间的交流合作居多,与国外的研究机构交流合作较少,国外研究机构则与之相反。该领域以应用机器学习类方法、知识图谱构建等,在地质灾害防治、地震解释、石油与天然气勘查、固体矿产资源预测等方向进行的科学研究为研究热点,以深度学习、集成学习、智能平台搭建等为手段的地球演化过程中的重大地质事件研究、全球性气候变化、极地及海洋地质研究、数字地质建模及定量分析、地震预报、地灾易发性精准评估等为研究前沿。展开更多
文摘The present article outlines progress made in designing an intelligent information system for automatic management and knowledge discovery in large numeric and scientific databases, with a validating application to the CAST-NEONS environmental databases used for ocean modeling and prediction. We describe a discovery-learning process (Automatic Data Analysis System) which combines the features of two machine learning techniques to generate sets of production rules that efficiently describe the observational raw data contained in the database. Data clustering allows the system to classify the raw data into meaningful conceptual clusters, which the system learns by induction to build decision trees, from which are automatically deduced the production rules.
文摘There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of knowledge discovery and data mining has become an urgent problem to be solved. On the base of analysis and study of existing research results, the united model of knowledge discovery state space （UMKDSS） is presented, and the structured data mining and the complex type data mining are associated together. UMKDSS can provide theoretical guidance for complex type data mining. An application example of UMKDSS is given at last.
文摘Important Dates Submission due November 15, 2005 Notification of acceptance December 30, 2005 Camera-ready copy due January 10, 2006 Workshop Scope Intelligence and Security Informatics (ISI) can be broadly defined as the study of the development and use of advanced information technologies and systems for national and international security-related applications. The First and Second Symposiums on ISI were held in Tucson,Arizona,in 2003 and 2004,respectively. In 2005,the IEEE International Conference on ISI was held in Atlanta,Georgia. These ISI conferences have brought together academic researchers,law enforcement and intelligence experts,information technology consultant and practitioners to discuss their research and practice related to various ISI topics including ISI data management,data and text mining for ISI applications,terrorism informatics,deception detection,terrorist and criminal social network analysis,crime analysis,monitoring and surveillance,policy studies and evaluation,information assurance,among others. We continue this stream of ISI conferences by organizing the Workshop on Intelligence and Security Informatics (WISI’06) in conjunction with the Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD’06). WISI’06 will provide a stimulating forum for ISI researchers in Pacific Asia and other regions of the world to exchange ideas and report research progress. The workshop also welcomes contributions dealing with ISI challenges specific to the Pacific Asian region.
基金partially supported by the Overseas Research Scholar Fund from Zhejiang University of Technology.
文摘Knowledge discovery from data directly can hardly avoid the fact that it is biased towards the collected experimental data, whereas, expert systems are always baffled with the manual knowledge acquisition bottleneck. So it is believable that integrating the knowledge embedded in data and those possessed by experts can lead to a superior modeling approach. Aiming at the classification problems, a novel integrated knowledge-based modeling methodology, oriented by experts and driven by data, is proposed. It starts from experts identifying modeling parameters, and then the input space is partitioned followed by fuzzification. Afterwards, single rules are generated and then aggregated to form a rule base, on which a fuzzy inference mechanism is proposed. The experts are allowed to make necessary changes on the rule base to improve the model accuracy. A real-world application, welding fault diagnosis, is presented to demonstrate the effectiveness of the methodology.
文摘人工智能科学(Artificial Intelligence for Science,AI4S)作为近年来兴起的交叉学科范式,通过现代信息技术,以数据驱动的方式推动科学发现与知识服务创新。立足图书馆事业发展,从图书馆学视角去认知什么是AI4S、洞察AI4S与发展图书馆服务的关系、拥抱AI4S带给图书馆服务的变革影响等内容具有重要价值。研究发现,AI4S与图书馆发展有着双向赋能的耦合逻辑链路。AI4S已在图书馆界得到了应用,在服务模式、服务能力、服务价值等方面深刻地变革影响着图书馆服务。
文摘为研究地质学领域的大数据和人工智能研究现状、热点和前沿,在中国知网(CNKI)核心期刊和Web of Science(WoS)核心数据库收集了2000—2022年相关中文文献3600篇、英文文献1803篇,利用社区结构分析软件CiteSpace,从合作作者、研究国家、研究机构、关键词聚类、关键词时空分布图谱等进行可视化分析,并统计了2021—2022年间,地质学领域国际顶级期刊(综合影响因子10以上)的文献进行前沿分析。分析结果表明,近10年内该研究领域全球累计发文量激增,以中国为代表的亚洲国家和以美国为代表的欧美国家研究为主,双方累计发文量相差不大,论文中介中心性欧美国家普遍较高。我国研究机构之间的交流合作居多,与国外的研究机构交流合作较少,国外研究机构则与之相反。该领域以应用机器学习类方法、知识图谱构建等,在地质灾害防治、地震解释、石油与天然气勘查、固体矿产资源预测等方向进行的科学研究为研究热点,以深度学习、集成学习、智能平台搭建等为手段的地球演化过程中的重大地质事件研究、全球性气候变化、极地及海洋地质研究、数字地质建模及定量分析、地震预报、地灾易发性精准评估等为研究前沿。
